Development of an AI-enabled Behavioral and Community Health Engagement Device: Applications Across Diverse Populations

Artificial intelligence (AI) is increasingly adopted in behavioral and community engagement initiatives across populations, private industries, and public sectors. As costs continue to decline, the integration of AI into health engagement devices presents significant opportunities to enhance both behavioral and community health outcomes. This study proposes a flexible conceptual framework to guide the development of an AI-enabled device intended to support diverse populations, facilitate patient engagement, and strengthen community health initiatives. It identifies major components of the device’s architectural design and outlines strategies for assessing usability and feasibility. Guided by a customer discovery approach, qualitative findings reveal users’ perceptions of both the opportunities and challenges associated with AI-enabled behavioral and community health engagement. The results offer directions for further research and propose benchmark metrics to evaluate the device’s performance during future development. In conclusion, this study highlights anticipated challenges and outlines next steps for advancing research and development efforts.

Authors

Institutions

Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/icaibd64986.2025.11082021
Citations
1
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
1.54

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of an AI-enabled Behavioral and Community Health Engagement Device: Applications Across Diverse Populations

Howard Leung, Chenghua Li, Janni Leung, K.C.S. Kwok
1 citations
Digital Mental Health Interventions
1.54
article

Development of an AI-enabled Behavioral and Community Health Engagement Device: Applications Across Diverse Populations

Howard Leung, Chenghua Li, Janni Leung, K.C.S. Kwok
article en
1 citations

Abstract

Artificial intelligence (AI) is increasingly adopted in behavioral and community engagement initiatives across populations, private industries, and public sectors. As costs continue to decline, the integration of AI into health engagement devices presents significant opportunities to enhance both behavioral and community health outcomes. This study proposes a flexible conceptual framework to guide the development of an AI-enabled device intended to support diverse populations, facilitate patient engagement, and strengthen community health initiatives. It identifies major components of the device’s architectural design and outlines strategies for assessing usability and feasibility. Guided by a customer discovery approach, qualitative findings reveal users’ perceptions of both the opportunities and challenges associated with AI-enabled behavioral and community health engagement. The results offer directions for further research and propose benchmark metrics to evaluate the device’s performance during future development. In conclusion, this study highlights anticipated challenges and outlines next steps for advancing research and development efforts.

American Industrial Partners (United States) (US), Hang Seng University of Hong Kong (HK), University of Hong Kong (HK), University of Memphis (US)
Office of the Director, HORIZON EUROPE Health
Openalex Percentile: Top 15%
Digital Mental Health Interventions
1.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.